Biodiversity science and conservation alike require environmental indicators to understand species richness and predict species distribution patterns. The Dynamic Habitat Indices (DHIs) are a set of three indices that summarize annual productivity measures from satellite data for biodiversity applications, and include: a) cumulative annual productivity; b) minimum annual productivity; and c) variation in annual productivity. At global scales and in temperate regions the DHIs predict species diversity patterns well, but the DHIs have not been tested in the tropics, where higher levels of productivity lead to the saturation of many remotely sensed vegetation indices. Our goal was to explain bird species richness patterns based on the DHIs in tropical areas. We related the DHIs to species richness of resident landbirds for five guilds (forest, scrub, grassland, generalist, and all resident birds) based on a) species distribution model (SDM) maps for 217 species, and b) range map for 564 species across Thailand. We also quantified the relative importance of the DHIs in multiple regression models that included two measures of topography, and two climate metrics using multiple regression, best-subsets, and hierarchical partitioning analyses. We found that the three DHIs alone explained forest bird richness best (R2adj 0.61 for both SDM- and rangemap based richness; 0.15–0.54 for the other guilds). When combining the DHIs with topography and climate, the richness of both forest birds and all resident bird species was equally well explained (R2adj 0.85 and 0.67 versus 0.81 and 0.68). Among the three DHIs, cumulative annual productivity had the greatest explanatory power for all guilds based on SDM richness maps (R2adj 0.54–0.61). The strong relationship between the DHIs and bird species richness in Thailand suggests that the DHIs capture energy availability well and are useful in biodiversity assessments and potentially bird conservation in tropical areas.
Biodiversity science and conservation alike require environmental indicators to understand species richness and predict species distribution patterns. The Dynamic Habitat Indices (DHIs) are a set of three indices that summarize annual productivity measures from satellite data for biodiversity applications, and include: a) cumulative annual productivity; b) minimum annual productivity; and c) variation in annual productivity. At global scales and in temperate regions the DHIs predict species diversity patterns well, but the DHIs have not been tested in the tropics, where higher levels of productivity lead to the saturation of many remotely sensed vegetation indices. Our goal was to explain bird species richness patterns based on the DHIs in tropical areas. We related the DHIs to species richness of resident landbirds for five guilds (forest, scrub, grassland, generalist, and all resident birds) based on a) species distribution model (SDM) maps for 217 species, and b) range map for 564 species across Thailand. We also quantified the relative importance of the DHIs in multiple regression models that included two measures of topography, and two climate metrics using multiple regression, best-subsets, and hierarchical partitioning analyses. We found that the three DHIs alone explained forest bird richness best (R2adj 0.61 for both SDM- and rangemap based richness; 0.15–0.54 for the other guilds). When combining the DHIs with topography and climate, the richness of both forest birds and all resident bird species was equally well explained (R2adj 0.85 and 0.67 versus 0.81 and 0.68). Among the three DHIs, cumulative annual productivity had the greatest explanatory power for all guilds based on SDM richness maps (R2adj 0.54–0.61). The strong relationship between the DHIs and bird species richness in Thailand suggests that the DHIs capture energy availability well and are useful in biodiversity assessments and potentially bird conservation in tropical areas.
Identifying the factors that determine habitat suitability and hence patterns of wildlife abundances
over broad spatial scales is important for conservation. Ecosystem productivity is a key aspect of habitat
suitability, especially for large mammals. Our goals were to a) explain patterns of moose (Alces alces)
abundance across Russia based on remotely sensed measures of vegetation productivity using Dynamic
Habitat Indices (DHIs), and b) examine if patterns of moose abundance and productivity difered before
and after the collapse of the Soviet Union. We evaluated the utility of the DHIs using multiple regression
models predicting moose abundance by administrative regions. Univariate models of the individual
DHIs had lower predictive power than all three combined. The three DHIs together with environmental
variables, explained 79% of variation in moose abundance. Interestingly, the predictive power of the
models was highest for the 1980s, and decreased for the two subsequent decades. We speculate that
the lower predictive power of our environmental variables in the later decades may be due to increasing
human infuence on moose densities. Overall, we were able to explain patterns in moose abundance in
Russia well, which can inform wildlife managers on the long-term patterns of habitat use of the species.
Identifying the factors that determine habitat suitability and hence patterns of wildlife abundances
over broad spatial scales is important for conservation. Ecosystem productivity is a key aspect of habitat
suitability, especially for large mammals. Our goals were to a) explain patterns of moose (Alces alces)
abundance across Russia based on remotely sensed measures of vegetation productivity using Dynamic
Habitat Indices (DHIs), and b) examine if patterns of moose abundance and productivity difered before
and after the collapse of the Soviet Union. We evaluated the utility of the DHIs using multiple regression
models predicting moose abundance by administrative regions. Univariate models of the individual
DHIs had lower predictive power than all three combined. The three DHIs together with environmental
variables, explained 79% of variation in moose abundance. Interestingly, the predictive power of the
models was highest for the 1980s, and decreased for the two subsequent decades. We speculate that
the lower predictive power of our environmental variables in the later decades may be due to increasing
human infuence on moose densities. Overall, we were able to explain patterns in moose abundance in
Russia well, which can inform wildlife managers on the long-term patterns of habitat use of the species.
Ecotourism is developing rapidly in biodiversity hotspots worldwide, but there is limited and mixed
empirical evidence that ecotourism achieves positive biodiversity outcomes. We assessed whether ecotourism
influenced forest loss rates and trajectories from 2000 to 2017 in Himalayan temperate forests. We compared forest
loss in 15 ecotourism hubs with nonecotourism areas in 4 Himalayan countries. We used matching statistics to
control for local-level determinants of forest loss, for example, population density, market access, and topography.
None of the ecotourism hubs was free of forest loss, and we found limited evidence that forest-loss trajectories in
ecotourism hubs were different from those in nonecotourism areas. In Nepal and Bhutan, differences in forest loss
rates between ecotourism hubs and matched nonecotourism areas did not differ significantly, and the magnitude
of the estimated effect was small. In India, where overall forest loss rates were the lowest of any country in
our analysis, forest loss rates were higher in ecotourism hubs than in matched nonecotourism areas. In contrast,
in China, where overall forest loss rates were highest, forest loss rates were lower in ecotourism hubs than
where there was no ecotourism. Our results suggest that the success of ecotourism as a forest conservation
strategy, as it is currently practiced in the Himalaya, is context dependent. In a region with high deforestation
pressures, ecotourism may be a relatively environmentally friendly form of economic development relative to
other development strategies. However, ecotourism may stimulate forest loss in regions where deforestation rates
are low.
Ecotourism is developing rapidly in biodiversity hotspots worldwide, but there is limited and mixed
empirical evidence that ecotourism achieves positive biodiversity outcomes. We assessed whether ecotourism
influenced forest loss rates and trajectories from 2000 to 2017 in Himalayan temperate forests. We compared forest
loss in 15 ecotourism hubs with nonecotourism areas in 4 Himalayan countries. We used matching statistics to
control for local-level determinants of forest loss, for example, population density, market access, and topography.
None of the ecotourism hubs was free of forest loss, and we found limited evidence that forest-loss trajectories in
ecotourism hubs were different from those in nonecotourism areas. In Nepal and Bhutan, differences in forest loss
rates between ecotourism hubs and matched nonecotourism areas did not differ significantly, and the magnitude
of the estimated effect was small. In India, where overall forest loss rates were the lowest of any country in
our analysis, forest loss rates were higher in ecotourism hubs than in matched nonecotourism areas. In contrast,
in China, where overall forest loss rates were highest, forest loss rates were lower in ecotourism hubs than
where there was no ecotourism. Our results suggest that the success of ecotourism as a forest conservation
strategy, as it is currently practiced in the Himalaya, is context dependent. In a region with high deforestation
pressures, ecotourism may be a relatively environmentally friendly form of economic development relative to
other development strategies. However, ecotourism may stimulate forest loss in regions where deforestation rates
are low.
Remotely sensed data can estimate terrestrial productivity more consistently and comprehensively across large
areas than field observations. However, questions remain how species richness and abundances are related to
terrestrial productivity in different biogeographic realms. The Dynamic Habitat Indices (DHIs) are a set of three
remote sensing indices each related to a key biodiversity productivity hypothesis (i.e., available energy proxied by
the annual cumulative productivity, environmental stress proxied by the minimum productivity throughout the
year, and environmental stability proxied by the annual coefficient of variation in productivity). Here, we quantify
the relevance of each hypothesis globally and for different biogeographic realms using models of species richness
for three taxa (amphibians, birds, and mammals) derived from IUCN species range maps. Using parameterized
generalized additive models (GAM’s) we found that the available energy hypothesis was the best individual
index explain 37–43% of the variation in species richness globally with the best models for amphibians and
worst for mammal richness. Examining the residuals of these GAMS indicated that adding the environmental
stress hypothesis explained 0–22% additional variance, especially in the Nearctic where large amounts of snow
and ice are prevalent and environmental conditions deteriorate during winter. The addition of the environmental
stability hypothesis generally explained more variance than the environmental stress hypothesis, especially in
the Neartic and Paleartic and for birds however, in certain cases, the environmental stress hypothesis explains
more variance at the realm scale.
Remotely sensed data can estimate terrestrial productivity more consistently and comprehensively across large
areas than field observations. However, questions remain how species richness and abundances are related to
terrestrial productivity in different biogeographic realms. The Dynamic Habitat Indices (DHIs) are a set of three
remote sensing indices each related to a key biodiversity productivity hypothesis (i.e., available energy proxied by
the annual cumulative productivity, environmental stress proxied by the minimum productivity throughout the
year, and environmental stability proxied by the annual coefficient of variation in productivity). Here, we quantify
the relevance of each hypothesis globally and for different biogeographic realms using models of species richness
for three taxa (amphibians, birds, and mammals) derived from IUCN species range maps. Using parameterized
generalized additive models (GAM’s) we found that the available energy hypothesis was the best individual
index explain 37–43% of the variation in species richness globally with the best models for amphibians and
worst for mammal richness. Examining the residuals of these GAMS indicated that adding the environmental
stress hypothesis explained 0–22% additional variance, especially in the Nearctic where large amounts of snow
and ice are prevalent and environmental conditions deteriorate during winter. The addition of the environmental
stability hypothesis generally explained more variance than the environmental stress hypothesis, especially in
the Neartic and Paleartic and for birds however, in certain cases, the environmental stress hypothesis explains
more variance at the realm scale.
The thermal environment limits species ranges through its influence on physiology and resource distributions
and thus affects species richness patterns over broad spatial scales. Understanding how temperature drives
species richness patterns is particularly important in the context of global change and for effective conservation
planning. Landsat 8's Thermal Infrared Sensor (TIRS) allows direct mapping of temperature at moderate spatial
resolutions (100 m, downscaled by the USGS to 30 m), overcoming limitations inherent in coarse interpolated
weather station data that poorly capture fine-scale temperature patterns over broad areas. TIRS data thus offer
the unique opportunity to understand how the thermal environment influences species richness patterns. Our
aim was to develop and assess the ability of TIRS-based temperature metrics to predict patterns of winter bird
richness across the conterminous United States during winter, a period of marked temperature stress for birds.
We used TIRS data from 2013-2018 to derive metrics of relative temperature and intra-seasonal thermal heterogeneity.
To quantify winter bird richness across the conterminous US, we tabulated the richness only for
resident bird species, i.e., those species that do not move between the winter and breeding seasons, from the
North American Breeding Bird Survey, the most extensive survey of birds in the US. We expected that relative
temperature and thermal heterogeneity would have strong positive associations with winter bird richness because
colder temperatures heighten temperature stress for birds, and thermal heterogeneity is a proxy for
thermal niches and potential thermal refugia that can support more species. We further expected that both the
strength of the effects and the relative importance of these variables would be greater for species with greater
climate sensitivity, such as small-bodied species and climate-threatened species (i.e., those with large discrepancies
between their current and future distributions following projected climate change). Consistent with
our predictions, relative temperature and thermal heterogeneity strongly positively influenced winter bird
richness patterns, with statistical models explaining 37.3% of the variance in resident bird richness. Thermal
heterogeneity was the strongest predictor of small-bodied and climate-threatened species in our models, whereas
relative temperature was the strongest predictor of large-bodied and climate-stable species. Our results demonstrate
the important role that the thermal environment plays in governing winter bird richness patterns and
highlight the previously underappreciated role that intra-seasonal thermal heterogeneity may have in supporting
high winter bird species richness. Our findings thus illustrate the exciting potential for TIRS data to guide
conservation planning in an era of global change.
Habitat loss is the primary driver of biodiversity decline worldwide, but the effects of fragmentation (the spatial
arrangement of remaining habitat) are debated. We tested the hypothesis that forest fragmentation sensitivity—
affected by avoidance of habitat edges—should be driven by historical exposure to, and therefore species’
evolutionary responses to disturbance. Using a database containing 73 datasets collected worldwide (encompassing
4489 animal species), we found that the proportion of fragmentation-sensitive species was nearly three times
as high in regions with low rates of historical disturbance compared with regions with high rates of disturbance
(i.e., fires, glaciation, hurricanes, and deforestation). These disturbances coincide with a latitudinal gradient
in which sensitivity increases sixfold at low versus high latitudes. We conclude that conservation efforts to limit
edges created by fragmentation will be most important in the world’s tropical forests.
While walking through a forest in spring we often marvel at the vivid greenness, listen to birdsong, and mind our steps in order not to get into a spider’s web. Enjoying the moment, we usually do not think about the complexity of this environment, nor the intertwined relations among all of its elements. However, what slips our attention is not going unrecognized by Maia Persche – a Master’s candidate in the SILVIS lab. In her research, Maia seeks to discern the role of topography in the timing of vegetation growth onset within forest, and to understand how topographic position potentially shapes songbird habitat.
Spring leaf emergence on a hillside in Baxter’s Hollow
To gain insight into these questions, Maia undertook the challenging tasks of measuring tree phenology, and conducting invertebrate and bird surveys in her study area in the Baraboo Hills of Southern Wisconsin. In order to relate these data to each other, each type of survey was carried out at the same 70 locations during narrow time windows throughout the season. Tree phenology surveys occurred in April and May, and invertebrate and bird surveys were repeated throughout the bird breeding season, or until the end of July. At each location, additional data was collected on temperature, tree species composition, and site characteristics. Over the course of two field seasons, she detected 53 insectivorous bird species, and tracked the seasonal abundance of common invertebrate orders (Lepidoptera, Araneae, Hemiptera, Hymenoptera, Diptera and Coleoptera).
Early May at an upland study site in Devil’s Lake State Park
Based on only a portion of measurements collected, Maia has already drawn some interesting preliminary conclusions. Trees leafed out slightly later in stream gorges than in uplands, and although invertebrate biomass was related to tree phenology, it did not appear to follow a predictable yearly pattern. However, sheltered stream gorges supporteded high invertebrate biomass during the mid- and late summer. This could be important for double-brooded bird species that still have active nests in July and can be limited by food availability in some habitats. Overall, stream gorges supported the highest bird species richness, perhaps due to stable food resources or habitat complexity. Also, a strong association has become evident between particular tree species and invertebrate orders, suggesting that tree composition may be more important than topographic context for some folivorous invertebrates.
Louisiana Waterthrush banded at Baxter’s Hollow
Under shifting climate conditions in deciduous forests, it is important to identify areas where habitat quality for species is likely to remain high. To assess bird territory quality in different topographic situations, Maia used feather growth bar analysis for a few widely distributed forest species (Wood Thrush, Red-eyed Vireo, and Ovenbird). She captured birds throughout her study area using mist nets, playback calls, and bird models. She then banded the birds, took structural measurements, and pulled one tail feather. Growth bars, or horizontal bands along the feather, correspond to diet richness of the bird while the feather was growing, and will be used to assess social dominance and habitat quality. Although this approach provides a detailed look at habitat quality, it is also the most difficult to carry out in the field.
Maia has collected a large amount of data, and analyzing the relationships among different factors and trophic levels is somewhat daunting, but she approaches it with great enthusiasm. Maia is currently working to determine how bird territory density varies according to topographic context. It is definitively worth staying tuned to see what new results Maia uncovers!
The Caucuses region (encompassing parts of Russia, Georgia, Armenia and Azerbaijan) has experienced extreme political upheavals. The collapse of the Soviet Union meant that the four countries became sovereign. Their powerful neighbors — Russia, Iran and Turkey – maintained strong geopolitical interests in the newly independent nations of Georgia, Armenia and Azerbaijan. As a result, the Caucasus has experienced four armed conflicts since 1991. In light of such extreme social and political disruption, Johanna wanted to know how cropland and forests had changed.
Figure 1: Land cover/ land use map of the Caucasus.
From previous research, some by former SILVIS lab members Drs. Mihai Nita and Catalina Munteanu, we know that some areas in Eastern Europe saw rapid cropland abandonment after the USSR collapsed. Other areas experienced forest clearing during the soviet era, and forest regrowth afterwards. Why do countries that are ostensibly similar geopolitically show such a wide range of land use outcomes?
“I want to make a clear link between land use and socio-political changes, but to do that you first have to describe where and when the land use changes have taken place.” Johanna says. To do that, she used Landsat imagery from 1987 to 2015 and mapped changes in land use and land cover.
Johanna found that there was some cropland abandonment in the Caucasus, particularly during the transition period in the 1990s and the time of armed conflicts. However, the cropland abandonment rate is far lower than the one apparent in eastern European countries that also experienced the breakdown of the Soviet Union. She has also found that forest as stayed surprisingly steady during the study period in the Caucasus.
Figure 2: Coniferous and mixed forest in Borjomi, Georgia. (Picture: V.Radeloff)
Her findings are rather surprising, since we expect political instability to interfere with cropland, and to make forests vulnerable for illegal harvesting. But in the Caucasus, Johanna explains, the steep, inaccessible terrain may have protected the forests from large clear cuts; even though the extracting of single valuable trees is widespread. Cropland, on the other hand is related to demand for food: cultivation continued wherever possible, unless we find armed conflicts in the region.
Figure 3: Preliminary results of abandoned arable land in Chechnya between 1987 and 2015
“What I can say is that land use patterns and outcomes are extremely dependent on the local context, especially in such a diverse region like the Caucasus” Johanna cautioned.
During the Pleistocene, red fox (Vulpes vulpes) populations in North America were isolated in glacial refugia
and diverged into 3 major lineages: the Nearctic-Eastern subclade of eastern Canada, the Nearctic-Mountain
subclade of the western mountains, and the Holarctic clade of Alaska. Following glacial retreats, these genetically
distinct populations of foxes expanded into newly available habitat. Along with subsequent translocation from fur
farms, these expansions have resulted in red foxes now occupying most of the continent. The origin of foxes that
colonized the Great Lakes Region, however, remains unknown. Furthermore, it is unclear whether contemporary
populations inhabiting this region are the result of natural range expansion or if foxes released from fur farms
colonized the landscape in the 1900s. To determine the origin of red foxes in the Great Lakes Region, we collected
genetic samples from 3 groups: 1) contemporary wild foxes, 2) historical wild foxes collected before fur farming,
and 3) fur-farmed foxes from a contemporary fur farm. We constructed a network of mtDNA haplotypes to identify
phylogeographic relationships between the 3 sample groups, and examined genetic signatures of fur-farmed
foxes via the androgen receptor gene (AR) associated with tame phenotypes. Historical wild foxes demonstrated
natural colonization from all 3 major North American lineages, which converged within the Great Lakes Region,
and contemporary wild foxes maintained the historically high genetic diversity. Most contemporary wild foxes
also matched haplotypes of fur-farmed foxes; however, AR was not useful in distinguishing fur-farm origins
in samples of contemporary wild foxes. Our results show that geographically disparate populations naturally
merged in the Great Lakes Region before fur-farmed foxes were introduced. Due to the historically high genetic
diversity in the Great Lakes Region, any introductions from fur farms likely contributed to, but did not create, the
genetic structure observed in this region.
Steller’s Jay that has been fitted with a radio-transmitter to track its movements and has been banded with a unique color combination, so it can be identified in the future without having to be re-captured.
Ph.D. student Kristin Brunk works in the old-growth redwoods of central California to understand the efficacy of current management for Steller’s Jays (Cyanocitta stelleri) and the implications of this management for the federally threatened Marbled Murrelet (Brachyramphus marmoratus). Both are native bird species in the redwoods, but Steller’s Jays are a synanthropic species, meaning they benefit from associating with humans, while Marbled Murrelet populations have severely declined. As populations of Steller’s Jays have increased, they have threatened the viability of Marbled Murrelet populations mainly through nest predation. Nowhere has this threat been more dire than in protected campground areas in remnant patches of old-growth forest. These areas have Steller’s Jay populations that are twice as high as in non-human dominated forests, and these campground areas also represent 60% of all remaining Marbled Murrelet nesting habitat in central California.
PhD student Kristin Brunk holds a banded Steller’s Jay before releasing.
Murrelet reproduction is naturally slow, as adults only produce one chick per year, but in central California where Steller’s Jay populations are subsidized by human foods, about 80% of Marbled Murrelet nests fail, due mostly to predation. Reducing corvid predation would help boost murrelet reproduction, which is believed to offer the highest probability of Marbled Murrelet population recovery in central California. In 2013, in an attempt to combat corvid predation, California State Parks implemented multiple non-lethal strategies to manage Steller’s Jays. These included improving trash management, deploying noxious murrelet mimic eggs to create taste aversion to murrelet eggs in corvids, and the “Crumb Clean” campaign, an effort to educate campers about the harm of feeding corvids and eliminate corvid access to camper food. The crumb clean campaign requires campers to properly store or dispose of all foodstuffs in their camp. Through the elimination of this food source in the campgrounds, the hope is that jay populations will decrease, allowing more murrelet nests to succeed. Brunk’s research focuses on comparing jay density, home range size, body condition, and diet between pre- and post-management jay populations to determine if these management strategies have been successful.
The aftermath of Steller’s Jays and other wildlife accessing food that has not been properly stowed by campers at a campsite in Big Basin State Park, where Kristin conducts her field work.
Brunk focuses her work within the campgrounds of Big Basin Redwoods State Park by capturing Steller’s Jays in mist nets. Once she has captured a jay, Brunk takes a tail feather sample to determine the bird’s body condition and a flight feather sample to determine what the bird has been eating. Body condition is determined by measuring feather growth bars, and Brunk deciphers how much human food the jays eat by performing stable isotope analyses on flight feather samples. Each jay is also banded with a unique color combination, so individuals can be identified without re-capturing them, and males are fitted with a backpack-mounted radio-transmitter. By tracking birds with radio-transmitters, Brunk is able to understand how jay home range sizes have changed since management started. Despite a perpetual battle of wits with the extremely intelligent Steller’s Jays, Brunk has successfully banded about 85% of the jays in her study area.
In addition to her research, Brunk is also incredibly active in education and outreach throughout her study area. She gives talks at Big Basin Campfire Programs to educate the public about Marbled Murrelets and Steller’s Jays. Brunk conducts banding demonstrations so campers can see exactly how she captures the jays, and they can often participate in the release of banded jays. And as she walks through the campgrounds tracking birds with radio-transmitters, she frequently answers campers’ questions about the giant metal antenna she is carrying. Brunk works hard to foster good relationships with the other users of her study area and is passionate about sharing her work to promote better public understanding of management initiatives such as the crumb clean campaign.
The Crumb Clean Campaign is an effort in Big Basin and all the other California State Parks to remind campers to pick up all their trash and every crumb of food, so jays and other potentially problematic critters won’t have access to human foods.
Brunk plans to complete one more field season in 2019, but her research is far from over. Brunk is also working to evaluate a Habitat Conservation Plan (HCP) and its effectiveness at conserving Marbled Murrelet habitat on private land. Habitat Conservation Plans are a commonly used management strategy, with over 1000 HCPs currently active, but the efficacy of these plans has not been well-tested. Brunk hopes to determine if HCPs are an effective management technique, using the Marbled Murrelet as a case study. Overall, Brunk’s research aims to understand the effectiveness of management strategies and conservation of federally threatened species. Ultimately, what she discovers will be used directly in adaptive management strategies that will be paramount in preventing the extinction of the Marbled Murrelet. Along the way, Brunk hopes to uncover strategies and techniques that will apply to the conservation of other species in the future.
